Evaluation of reconstruction techniques for lung single photon emission tomography: a Monte Carlo study

Nucl Med Commun. 2007 Dec;28(12):929-36. doi: 10.1097/MNM.0b013e3282f1acac.


Background: In studies of the distribution of lung function, the image quality of lung single photon emission computed tomography (SPECT) is important and one factor influencing it is the reconstruction algorithm.

Aim: To systematically evaluate ordered subsets expectation maximization (OSEM) and compare it with filtered back-projection (FBP) for lung SPECT with Tc.

Methods: The evaluation of the number of iterations used in OSEM was based on the image quality parameter contrast. The comparison between OSEM and FBP was based on trade-off plots between statistical noise and spatial resolution for different filter parameters, collimators and count-levels. A Monte Carlo technique was used to simulate SPECT studies of a digital thorax phantom containing two sets of activity: one with a homogeneous activity distribution within the lungs and the other with superposed high- and low-activity objects. Statistical noise in the reconstructed images was calculated as the coefficient of variation (CV) and spatial resolution as full width at half-maximum (FWHM).

Results: For the configuration studied, the OSEM reconstruction in combination with post-filtering should be used in lung SPECT studies with at least 60 MLEM equivalent iterations. Compared to FBP the spatial resolution was improved by about 1 mm. For a constant level of CV, a four-fold increase in count level resulted in an increased resolution of about 2 mm. Spatial resolution and cut-off frequency depends on what value of noise in the image is acceptable also increased by using a low-energy, high-resolution collimator for CV values above 3%. The choice of noise-reducing filter and cut-off frequency depends on what value of noise in the image is acceptable.

Publication types

  • Comparative Study
  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Computer Simulation
  • Humans
  • Image Enhancement / methods*
  • Image Interpretation, Computer-Assisted / methods*
  • Lung / diagnostic imaging*
  • Models, Biological*
  • Models, Statistical
  • Monte Carlo Method
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Tomography, Emission-Computed, Single-Photon / methods*